PhD Position in AI-Driven Multimodal Biomaterials Analysis

Develop AI models to analyze and predict biomaterial performance using advanced imaging and machine learning.

Best for:Best for candidates with a strong background in biomedical engineering, computer science, or materials science, passionate about AI-driven imaging and predictive modeling of biomaterials.

University of Oslo · Oslo, Norway · R1 · First-stage researcher

More professors at University of Oslo

AI-driven multimodal analysisBiomaterial scaffold characterizationQuantitative 2D/3D imaging of tissuesPredictive modeling of cell distributionStandardization of biomedical imaging data

Deadline

Oct 20, 2026

5 days

Funding

—

3 years (standard PhD duration in Norway)

Start date

flexible (commencement expected after hiring)

Full-time

Location

Oslo

Norway

Overview

This PhD position at the University of Oslo focuses on integrating advanced imaging techniques—such as micro/nanoCT, confocal microscopy, and SEM—with computational methods like computer vision and machine learning. The goal is to create standardized AI-driven tools that link structural, mechanical, and biological properties to biomaterial performance and tissue regeneration. The successful candidate will work on quantitative analysis of biological tissues, scaffold characterization, and predictive modeling of cell distribution in regenerative biomaterials. Interdisciplinary training in biomaterials, imaging, and machine learning will be provided.

AI in biomaterialsMachine learning for medical imagingMicro/nanoCT analysisConfocal microscopyBiomaterial scaffoldsPredictive modelingQuantitative image analysisTissue regeneration

What you'll do

Conduct quantitative 2D and 3D analysis of biological tissues using advanced imaging techniques like nanoCT and SEM.
Develop and apply computational methods for characterizing fibrous biomaterial scaffolds, including porosity and fiber architecture.
Standardize and analyze biomedical imaging data using machine learning and AI-driven predictive models.
Predict cell and exosome distribution in regenerative biomaterials using AI-based modeling techniques.
Collaborate on interdisciplinary research projects involving biomaterials, imaging, and computational analysis.
Present research findings at conferences and publish results in peer-reviewed journals.

Requirements

Degree required: Master's degree in Biomedical Engineering, Computer Science, Materials Science, or a related field.

Degree offered: PhD

Language: English; proficiency suitable for academic research and publication

Instruction: English

Required skills

Experience with advanced imaging techniques (e.g., micro/nanoCT, confocal microscopy, SEM).
Proficiency in computational methods, computer vision, and machine learning.
Strong programming skills (e.g., Python, R).
Background in quantitative data analysis and modeling.

Nice to have

Experience with AI/ML frameworks (e.g., TensorFlow, PyTorch).Familiarity with biomedical data processing and analysis tools.Knowledge of biomaterial characterization techniques.

Eligibility

No specific nationality or residency restrictions mentioned.
Open to applicants with relevant academic background and research experience.

Funding & terms

Type

Unknown

Amount

—

Duration

3 years (standard PhD duration in Norway)

Programme

University of Oslo

How to apply

Deadline: 2026-10-20 (Europe/Oslo)

Applicants must submit their application through the official University of Oslo job portal. Required documents include a CV, cover letter, academic transcripts, and a research proposal. Three letters of recommendation are also required.

Documents required